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Framework for the ISO 52016 standard accuracy prediction based on the in-depth sensitivity analysis

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  • Zakula, Tea
  • Badun, Nikola
  • Ferdelji, Nenad
  • Ugrina, Ivo

Abstract

We present here a comprehensive study on the accuracy of ISO 52016-1:2017 standard (the Standard), and provide a novel, widely applicable framework for its assessment. The global sensitivity analysis and predictive modeling have been utilized to explore the intricacies of differences between the Standard and dynamic simulations in TRNSYS. The study includes more than 147 thousand cases with diverse combinations of building characteristics and all international climate zones. The main conclusion is that the Standard has good accuracy in the calculation of heating energy needs, while it is much less accurate in the calculation of cooling energy needs. For climates in which heating is dominant, 100% of cases had acceptable accuracy; in contrast, only 30–70% of cases in moderate climates had an acceptable accuracy. Consequently, we propose improvements to the Standard, suggesting that considerable benefits could be obtained if the variability of window properties based on the boundary conditions at each time step is implemented. The proposed method results in significant improvements since the number of acceptable cases for cooling in moderate climates has increased to 75–100%. This has been quantified for a great variety of window properties and for all climates. An online tool has been provided, enabling the estimation of the expected relative difference between the Standard and TRNSYS for a specific building.

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  • Zakula, Tea & Badun, Nikola & Ferdelji, Nenad & Ugrina, Ivo, 2021. "Framework for the ISO 52016 standard accuracy prediction based on the in-depth sensitivity analysis," Applied Energy, Elsevier, vol. 298(C).
    • Handle: RePEc:eee:appene:v:298:y:2021:i:c:s0306261921005407
    DOI: 10.1016/j.apenergy.2021.117089
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    References listed on IDEAS

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    1. Ilaria Ballarini & Andrea Costantino & Enrico Fabrizio & Vincenzo Corrado, 2020. "A Methodology to Investigate the Deviations between Simple and Detailed Dynamic Methods for the Building Energy Performance Assessment," Energies, MDPI, vol. 13(23), pages 1-19, November.
    2. H. Christopher Frey & Sumeet R. Patil, 2002. "Identification and Review of Sensitivity Analysis Methods," Risk Analysis, John Wiley & Sons, vol. 22(3), pages 553-578, June.
    3. Heiselberg, Per & Brohus, Henrik & Hesselholt, Allan & Rasmussen, Henrik & Seinre, Erkki & Thomas, Sara, 2009. "Application of sensitivity analysis in design of sustainable buildings," Renewable Energy, Elsevier, vol. 34(9), pages 2030-2036.
    4. Zakula, Tea & Bagaric, Marina & Ferdelji, Nenad & Milovanovic, Bojan & Mudrinic, Sasa & Ritosa, Katia, 2019. "Comparison of dynamic simulations and the ISO 52016 standard for the assessment of building energy performance," Applied Energy, Elsevier, vol. 254(C).
    5. Li, Hangxin & Wang, Shengwei & Cheung, Howard, 2018. "Sensitivity analysis of design parameters and optimal design for zero/low energy buildings in subtropical regions," Applied Energy, Elsevier, vol. 228(C), pages 1280-1291.
    6. Yıldız, Yusuf & Arsan, Zeynep Durmuş, 2011. "Identification of the building parameters that influence heating and cooling energy loads for apartment buildings in hot-humid climates," Energy, Elsevier, vol. 36(7), pages 4287-4296.
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    1. Giovanna De Luca & Franz Bianco Mauthe Degerfeld & Ilaria Ballarini & Vincenzo Corrado, 2021. "Accuracy of Simplified Modelling Assumptions on External and Internal Driving Forces in the Building Energy Performance Simulation," Energies, MDPI, vol. 14(20), pages 1-22, October.
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    3. Amin Nouri & Christoph van Treeck & Jérôme Frisch, 2024. "Sensitivity Assessment of Building Energy Performance Simulations Using MARS Meta-Modeling in Combination with Sobol’ Method," Energies, MDPI, vol. 17(3), pages 1-24, January.

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